• Title, Summary, Keyword: 정점 집합 데이터

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대용량 그래프에서의 삼각형 검색 연구: 알고리즘과 응용

  • Park, Ha-Myeong;Gang, Yu
    • Information and Communications Magazine
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    • v.31 no.11
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    • pp.58-66
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    • 2014
  • 본 고에서는 다양한 네트워크를 표현하는 그래프에서 삼각형을 검색하는 알고리즘과 그 응용을 다룬다. 삼각형은 그래프에서 서로가 연결된 세 정점의 집합을 의미한다. 삼각형 검색 문제는 폭 넓은 응용이 가능하기 때문에 데이터 마이닝, 네트워크 분석 등 다양한 분야에서 중요하고 기본적인 문제로서 인식되어왔다. 삼각형 검색 문제의 중요성이 널리 인식되면서 여러 알고리즘이 제안 되어 왔지만, 최근의 소셜 네트워크, 웹 등의 크기가 방대해 기존의 방법은 이러한 네트워크를 분석하기가 사실상 불가능하다. 최근 맵리듀스를 활용한 분산/병렬 처리를 통해 대용량 그래프에서 삼각형을 검색하는 알고리즘들이 여럿 제안되었다. 본 논문에서는 지금까지 제안된 알고리즘들을 설명하고 삼각형 검색의 응용에 대해서 소개한다.

Fast Triangulation of Terrain Data through Unique Point Extraction (특이점 추출을 통한 지형데이터의 빠른 삼각망 생성)

  • 전경훈;구자영
    • Korean Journal of Remote Sensing
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    • v.19 no.6
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    • pp.457-464
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    • 2003
  • Triangulated irregular network is one of the most frequently used terrain modeling methods. It represents terrain precisely using only a small amount of data, and enables fast rendering of terrain. In this paper, ridges and valleys are extracted from the terrain, and used as a set of vertices for the construction of triangulated irregular network. An experiment shows the new method reduces the time for construction of the triangulated irregular network significantly with almost equal amount of induced error.

Approximate Top-k Subgraph Matching Scheme Considering Data Reuse in Large Graph Stream Environments (대용량 그래프 스트림 환경에서 데이터 재사용을 고려한 근사 Top-k 서브 그래프 매칭 기법)

  • Choi, Do-Jin;Bok, Kyoung-Soo;Yoo, Jae-Soo
    • The Journal of the Korea Contents Association
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    • v.20 no.8
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    • pp.42-53
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    • 2020
  • With the development of social network services, graph structures have been utilized to represent relationships among objects in various applications. Recently, a demand of subgraph matching in real-time graph streams has been increased. Therefore, an efficient approximate Top-k subgraph matching scheme for low latency in real-time graph streams is required. In this paper, we propose an approximate Top-k subgraph matching scheme considering data reuse in graph stream environments. The proposed scheme utilizes the distributed stream processing platform, called Storm to handle a large amount of stream data. We also utilize an existing data reuse scheme to decrease stream processing costs. We propose a distance based summary indexing technique to generate Top-k subgraph matching results. The proposed summary indexing technique costs very low since it only stores distances among vertices that are selected in advance. Finally, we provide k subgraph matching results to users by performing an approximate Top-k matching on the summary indexing. In order to show the superiority of the proposed scheme, we conduct various performance evaluations in diverse real world datasets.

The Design of Genetic Fuzzy Set Polynomial Neural networks based on Information Granules and Its Application of Multi -variables System (정보 입자 기반 유전론적 퍼지 집합 다항식 뉴럴네트워크 설계와 다변수 시스템으로의 응용)

  • Lee In-Tae;Oh Sung-Kwun;Kim Hyun-Ki;Seo Ki-Sung
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • pp.479-482
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    • 2005
  • 본 논문에서는 퍼지 뉴럴네트워크의 새로운 구조인 Fuzzy Set-based Polynomial Neural Networks(FSPNN)을 소개한다. 제안된 모델은 일반적인 최적화 방법과 정보 입자를 이용하여 네트워크를 설계한다. 최종 구조는 Fuzzy Set-based Polynomial Neuron(FSPN)을 기반으로 설계한 FPNN과 동일하다. 첫째로 FSPNS의 종합적인 설계방법(유전자 알고리즘을 이용한 최적 구조 탐색)에 대해 소개한다. FSPNN에 관계되는 입력변수의 개수, 후반부 다항식의 차수, 멤버쉽 함수의 수 그리고 입력변수 개수에 따른 입력변수를 유전자 알고리즘을 통하여 동조한다. 두 번째로, 입력 변수의 개별적인 퍼지 규칙 형성과 퍼지 공간 분할 및 삼각형 멤버쉽 함수의 초기 정점을 HCM 클러스터링을 통한 Information Granules로 정의한다. 또한 데이터 입자의 중심을 이용하여 후반부의 구조를 결정한다. 이 네트워크의 성능은 기존에 퍼지 또는 뉴로퍼지 모델링에서 실험된 모델링 표준치를 이용하여 평가한다.

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Point Cloud Data Driven Level of detail Generation in Low Level GPU Devices (Low Level GPU에서 Point Cloud를 이용한 Level of detail 생성에 대한 연구)

  • Kam, JungWon;Gu, BonWoo;Jin, KyoHong
    • Journal of the Korea Institute of Military Science and Technology
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    • v.23 no.6
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    • pp.542-553
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    • 2020
  • Virtual world and simulation need large scale map rendering. However, rendering too many vertices is a computationally complex and time-consuming process. Some game development companies have developed 3D LOD objects for high-speed rendering based on distance between camera and 3D object. Terrain physics simulation researchers need a way to recognize the original object shape from 3D LOD objects. In this paper, we proposed simply automatic LOD framework using point cloud data (PCD). This PCD was created using a 6-direct orthographic ray. Various experiments are performed to validate the effectiveness of the proposed method. We hope the proposed automatic LOD generation framework can play an important role in game development and terrain physic simulation.

Discovering Association Rules using Item Clustering on Frequent Pattern Network (빈발 패턴 네트워크에서 아이템 클러스터링을 통한 연관규칙 발견)

  • Oh, Kyeong-Jin;Jung, Jin-Guk;Ha, In-Ay;Jo, Geun-Sik
    • Journal of Intelligence and Information Systems
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    • v.14 no.1
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    • pp.1-17
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    • 2008
  • Data mining is defined as the process of discovering meaningful and useful pattern in large volumes of data. In particular, finding associations rules between items in a database of customer transactions has become an important thing. Some data structures and algorithms had been proposed for storing meaningful information compressed from an original database to find frequent itemsets since Apriori algorithm. Though existing method find all association rules, we must have a lot of process to analyze association rules because there are too many rules. In this paper, we propose a new data structure, called a Frequent Pattern Network (FPN), which represents items as vertices and 2-itemsets as edges of the network. In order to utilize FPN, We constitute FPN using item's frequency. And then we use a clustering method to group the vertices on the network into clusters so that the intracluster similarity is maximized and the intercluster similarity is minimized. We generate association rules based on clusters. Our experiments showed accuracy of clustering items on the network using confidence, correlation and edge weight similarity methods. And We generated association rules using clusters and compare traditional and our method. From the results, the confidence similarity had a strong influence than others on the frequent pattern network. And FPN had a flexibility to minimum support value.

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Integrity Assessment Models for Bridge Structures Using Fuzzy Decision-Making (퍼지의사결정을 이용한 교량 구조물의 건전성평가 모델)

  • 안영기;김성칠
    • Journal of the Korea Concrete Institute
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    • v.14 no.6
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    • pp.1022-1031
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    • 2002
  • This paper presents efficient models for bridge structures using CART-ANFIS (classification and regression tree-adaptive neuro fuzzy inference system). A fuzzy decision tree partitions the input space of a data set into mutually exclusive regions, each region is assigned a label, a value, or an action to characterize its data points. Fuzzy decision trees used for classification problems are often called fuzzy classification trees, and each terminal node contains a label that indicates the predicted class of a given feature vector. In the same vein, decision trees used for regression problems are often called fuzzy regression trees, and the terminal node labels may be constants or equations that specify the predicted output value of a given input vector. Note that CART can select relevant inputs and do tree partitioning of the input space, while ANFIS refines the regression and makes it continuous and smooth everywhere. Thus it can be seen that CART and ANFIS are complementary and their combination constitutes a solid approach to fuzzy modeling.